Method and device for realizing aviation communication interference analysis processing based on semantic recognition, processor and computer readable storage medium thereof

Abstract

The invention relates to a method for analyzing and processing aviation communication interference based on semantic recognition, which comprises the following steps of: issuing broadcast and aviation communication control tasks, automatically acquiring signal parameters, and establishing aviation communication voice interference characteristic words; after voice data is filtered, stream data is cut and stored into a plurality of files, and the files are used as data buffering in a transcription process; performing file transcription concurrent adjustment according to the computing power load condition of the voice transcription text process; and retrieving a voice transcribed text, substituting semantic feature words to carry out context inference comparison, and carrying out evidence collection and alarm on the interference frequency. By adopting the method and the device for realizing aviation communication interference analysis processing based on semantic recognition, the processor and the computer readable storage medium, the difficulty of manually processing multi-channel narrowband voice information is solved, and the problem that a frequency modulation broadcast frequency band and an aviation communication frequency band are partially adjacent and public, so that the processing efficiency is greatly improved is solved. And the capability of analyzing aviation communication interference caused by aging and illegal setting of broadcast service high-power equipment is realized.

Description

Technical Field

[0001] The present invention relates to the field of radio, in particular to the field of radio monitoring, and specifically refers to a method, device, processor and computer-readable storage medium thereof for realizing aviation communication interference analysis and processing based on semantic recognition. Background Art

[0002] With the development of radio monitoring technology, the real-time bandwidth of receivers is getting larger and larger, and the processor efficiency is getting higher and higher. 80M real-time bandwidth has become the mainstream product. Some high-end receivers have developed to 160M, 320M or even 500M real-time bandwidth, which makes 16-channel, 32-channel, and 64-channel narrowband monitoring gradually become a routine application. Traditional multi-channel narrowband monitoring, 24-hour control, manpower is unable to process such a large amount of voice data. The voice transcription text and feature word comparison retrieval implemented by software effectively improve the voice data processing capability. At the same time, in the practice of aviation communication frequency band special work, it was found that due to the FM broadcasting band and the aviation communication band, some frequencies are adjacent and shared, and the aging of high-power equipment in the broadcasting business and illegal station setting are the important reasons for the current aviation communication interference. Therefore, a method and system for aviation communication interference analysis based on semantic recognition greatly optimizes the efficiency of multi-channel narrowband voice information extraction and improves the practicality of interference detection. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and to provide a method, device, processor and computer-readable storage medium thereof for realizing aviation communication interference analysis and processing based on semantic recognition, which have the advantages of high efficiency, good practicality and wide application range.

[0004] In order to achieve the above-mentioned purpose, the method, device, processor and computer-readable storage medium thereof for realizing aviation communication interference analysis and processing based on semantic recognition of the present invention are as follows:

[0005] The method for analyzing and processing aviation communication interference based on semantic recognition is mainly characterized in that the method comprises the following steps:

[0006] (1) Issue broadcast and aviation communication control tasks, automatically obtain signal parameters, and establish aviation communication voice interference signatures;

[0007] (2) After the voice data is filtered, the stream data is cut and stored into several files, which serve as data buffers for the transcription process;

[0008] (3) Adjust the concurrency of file transcription based on the computing load of the voice transcription process;

[0009] (4) Retrieve the text of the voice transcription, bring in semantic feature words for contextual inference and comparison, and obtain evidence and issue an alarm for the interference frequency.

[0010] Preferably, the step (1) specifically comprises the following steps:

[0011] (1.1) When the voice on the aviation communication frequency is interfered by broadcasting, the broadcasting interference voice feature words are entered into the text retrieval database; a 24-hour continuous monitoring task of the broadcasting and aviation communication frequency band is issued, and the signal parameters exceeding the adaptive threshold are given;

[0012] (1.2) Send the frequency, bandwidth and signal modulation mode of the narrowband signal parameters to the monitoring receiver;

[0013] (1.3) For signal parameter changes caused by abnormal signals, automatically modify the multi-channel narrowband monitoring parameters and continue with step (1.2).

[0014] Preferably, the step (2) specifically comprises the following steps:

[0015] After the voice data is filtered, the PCM stream data is divided by time length and stored as WAV voice files according to the efficiency of the voice transcription process and the text size; the closed voice files are asynchronously uploaded through the URL address.

[0016] Preferably, the step (3) specifically comprises the following steps:

[0017] (3.1) Monitor server resources through ssh commands and establish an appropriate number of concurrent threads based on the computing load of the voice transcription process;

[0018] (3.2) If the thread is idle, retrieve the voice file for transcription; otherwise, wait for the thread to be idle.

[0019] Preferably, the step (4) specifically comprises the following steps:

[0020] Retrieve the text of voice transcription, bring in semantic feature words for context inference and comparison, collect evidence and alarm on interference frequency, list the frequency and time of interference, and replay voice files retroactively.

[0021] The main feature of the device for realizing aviation communication interference analysis and processing based on semantic recognition is that the device comprises:

[0022] a processor configured to execute computer executable instructions;

[0023] The memory stores one or more computer executable instructions. When the computer executable instructions are executed by the processor, the various steps of the method for analyzing and processing aviation communication interference based on semantic recognition are implemented.

[0024] The processor for implementing aviation communication interference analysis and processing based on semantic recognition has the main feature that the processor is configured to execute computer-executable instructions. When the computer-executable instructions are executed by the processor, the various steps of the above-mentioned method for implementing aviation communication interference analysis and processing based on semantic recognition are implemented.

[0025] The main feature of the computer-readable storage medium is that a computer program is stored thereon, and the computer program can be executed by a processor to implement the various steps of the above-mentioned method for analyzing and processing aviation communication interference based on semantic recognition.

[0026] The method, device, processor and computer-readable storage medium for analyzing and processing aviation communication interference based on semantic recognition of the present invention are adopted to solve the difficulty of manually processing multi-channel narrow-band voice information, and improve the ability to analyze aviation communication interference caused by the FM broadcasting band and the aviation communication band, the adjacent and public use of some frequencies, the aging of high-power equipment in the broadcasting business and illegal installation of stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is a flow chart of a method for analyzing and processing aviation communication interference based on semantic recognition.

[0028] Figure 2 It is the original speech data of the method for realizing aviation communication interference analysis and processing based on semantic recognition of the present invention.

[0029] Figure 3 This is the filtered data of the method for realizing aviation communication interference analysis and processing based on semantic recognition of the present invention.

[0030] Figure 4 This is a schematic diagram of the CPU and memory usage of the container virtual machine when two-way voice is simultaneously transcribed to text and five-way voice is simultaneously transcribed in the method for realizing aviation communication interference analysis and processing based on semantic recognition of the present invention.

[0031] Figure 5 This is a schematic diagram of the operating occupancy of the real physical CPU and memory of a single-core CPU server of the method for realizing aviation communication interference analysis and processing based on semantic recognition of the present invention when 5-channel voices are transcribed simultaneously.

[0032] Figure 6 A schematic diagram of broadband spectrum observation of the method for realizing aviation communication interference analysis and processing based on semantic recognition of the present invention.

[0033] Figure 7 The present invention is a schematic diagram of the contents of the speech transcription text of the method for realizing aviation communication interference analysis and processing based on semantic recognition. DETAILED DESCRIPTION

[0034] In order to more clearly describe the technical content of the present invention, further description is given below in conjunction with specific embodiments.

[0035] The method for analyzing and processing aviation communication interference based on semantic recognition of the present invention comprises the following steps:

[0036] (1) Issue broadcast and aviation communication control tasks, automatically obtain signal parameters, and establish aviation communication voice interference signatures;

[0037] (2) After the voice data is filtered, the stream data is cut and stored into several files, which serve as data buffers for the transcription process;

[0038] (3) Adjust the concurrency of file transcription based on the computing load of the voice transcription process;

[0039] (4) Retrieve the text of the voice transcription, bring in semantic feature words for contextual inference and comparison, and obtain evidence and issue an alarm for the interference frequency.

[0040] As a preferred embodiment of the present invention, the step (1) specifically comprises the following steps:

[0041] (1.1) When the voice on the aviation communication frequency is interfered by broadcasting, the broadcasting interference voice feature words are entered into the text retrieval database; a 24-hour continuous monitoring task of the broadcasting and aviation communication frequency band is issued, and the signal parameters exceeding the adaptive threshold are given;

[0042] (1.2) Send the frequency, bandwidth and signal modulation mode of the narrowband signal parameters to the monitoring receiver;

[0043] (1.3) For signal parameter changes caused by abnormal signals, automatically modify the multi-channel narrowband monitoring parameters and continue with step (1.2).

[0044] As a preferred embodiment of the present invention, the step (2) specifically comprises the following steps:

[0045] After the voice data is filtered, the PCM stream data is divided by time length and stored as WAV voice files according to the efficiency of the voice transcription process and the text size; the closed voice files are asynchronously uploaded through the URL address.

[0046] As a preferred embodiment of the present invention, the step (3) specifically comprises the following steps:

[0047] (3.1) Monitor server resources through ssh commands and establish an appropriate number of concurrent threads based on the computing load of the voice transcription process;

[0048] (3.2) If the thread is idle, retrieve the voice file for transcription; otherwise, wait for the thread to be idle.

[0049] As a preferred embodiment of the present invention, the step (4) specifically comprises the following steps:

[0050] Retrieve the text of voice transcription, bring in semantic feature words for context inference and comparison, collect evidence and alarm on interference frequency, list the frequency and time of interference, and replay voice files retroactively.

[0051] The device for implementing aviation communication interference analysis and processing based on semantic recognition of the present invention, wherein the device comprises:

[0052] a processor configured to execute computer executable instructions;

[0053] The memory stores one or more computer executable instructions. When the computer executable instructions are executed by the processor, the various steps of the method for analyzing and processing aviation communication interference based on semantic recognition are implemented.

[0054] The processor of the present invention is used to implement aviation communication interference analysis and processing based on semantic recognition, wherein the processor is configured to execute computer executable instructions. When the computer executable instructions are executed by the processor, the various steps of the above-mentioned method for implementing aviation communication interference analysis and processing based on semantic recognition are implemented.

[0055] The computer-readable storage medium of the present invention stores a computer program thereon, and the computer program can be executed by a processor to implement the various steps of the above-mentioned method for analyzing and processing aviation communication interference based on semantic recognition.

[0056] In a specific implementation manner of the present invention, a method and system for analyzing aviation communication interference based on semantic recognition are involved. The system is composed of central software, equipment services and monitoring receivers.

[0057] The present invention provides an aviation communication interference analysis method and system based on semantic recognition, wherein the method comprises the following steps:

[0058] (1) Issue broadcast and aviation communication control tasks, automatically obtain signal parameters, and establish aviation communication voice interference signatures;

[0059] (2) After the voice data is filtered, the stream data is cut and stored into several files, which serve as data buffers for the transcription process;

[0060] (3) Based on the computing load of the voice transcription process, adjust the file transcription concurrency and use computing resources reasonably;

[0061] (4) Retrieve the text of the voice transcription, bring in semantic feature words for contextual inference and comparison, and obtain evidence and issue an alarm for the interference frequency.

[0062] The step (1) specifically comprises the following steps:

[0063] (1.1) When the voice on the aviation communication frequency is interfered by the broadcasting sound, the broadcasting interference voice feature words are entered into the text retrieval database; a 24-hour continuous monitoring task of the broadcasting and aviation communication frequency band is issued, and the signal parameters exceeding the adaptive threshold are given; the signal parameters are calculated as follows:

[0064] a) Adaptive threshold calculation

[0065]

[0066] Where S is the broadband spectrum data, i traverses every element of S; N is the total number of intervals divided by S according to M sample points, j traverses every element of N; N j It is the average noise floor of the jth interval. The value of M depends on the signal bandwidth, usually M>signal bandwidth / resolution.

[0067] b) Signal parameters

[0068]

[0069] Among them, L is the threshold margin, which is generally 10, that is, the sensitivity of judging whether there is a signal must satisfy the signal-to-noise ratio ≥ 10dB; the signal bandwidth is the bandwidth where the peak amplitude drops by 3dB, and the signal frequency takes the symmetrical center value within the signal bandwidth; usually the modulation mode for broadcasting services is FM, and the modulation mode for aviation communications is AM.

[0070] When the voice on the aviation communication frequency is interfered with by broadcast sound, if there is a clear broadcast hourly time announcement and obvious broadcast sound keywords, the semantics of the voice can be entered into the feature word text library at any time as a basis for retrieval and comparison.

[0071] (1.2) Send the frequency, bandwidth and signal modulation mode of the narrowband signal parameters to the monitoring receiver;

[0072] The signal parameters captured in step (1.1), including frequency, bandwidth, and modulation mode, are sorted according to the signal-to-noise ratio and sent to the receiver.

[0073] (1.3) For signal parameter changes caused by abnormal signals, automatically modify the multi-channel narrowband monitoring parameters and continue with step (1.2);

[0074] If there is a signal change caused by an abnormal signal, all the changed signal parameters will be sent to the receiver.

[0075] The step (2) specifically comprises the following steps:

[0076] (2.1) After the voice data is filtered, the PCM stream data is divided by time length and stored as WAV voice files based on the efficiency of the voice transcription process and the size of the text; the closed voice files are asynchronously uploaded to the central software via the URL address file, so that the central transcription computing power and network bandwidth can be reasonably utilized.

[0077] Voice transcription will be affected by background noise and background music. The separation of voice and background sound sources is a relatively complicated process. In order to save resources and improve efficiency, this case does not involve sound source separation; only high-frequency noise reduction is performed through finite impulse response filtering to filter out high-frequency DC sound and background noise. Although some accuracy is lost, the human voice is highlighted to a certain extent, which improves the timeliness and accuracy of voice transcription text to a certain extent. The filtering process is as follows:

[0078] In order to reduce the high-frequency noise of voice data, a Hamming window is used. The sidelobe attenuation of the Hamming window is large, which can effectively reduce spectrum leakage. The amplitude response of the Hamming window fluctuates in the passband and stopband, and the accuracy loss of the signal part is acceptable. The window function is as follows:

[0079]

[0080] Where n is the sample index in the window and N is the length of the window. Let the filter length be N and the cutoff frequency be f c , sampling frequency f s , then the cut-off angular frequency:

[0081]

[0082] Filter coefficient h n for:

[0083]

[0084] The filter coefficients are then normalized:

[0085]

[0086] The following is the output signal after filtering by weighted summation of finite impulse response filtering:

[0087]

[0088] Among them, h is the filter coefficient, N is the filter length, x is the input speech sample, and y is the output sequence. Figure 2 is the original voice data, Figure 3 For the filtered data, high-frequency DC sound and some noise are filtered out.

[0089] PCM data stream does not contain parameters such as audio sampling rate, channel, bit rate, etc. WAV is a general lossless voice playback file. Voice transcription requires certain context scene derivation. If the data is too long and the text is too large, the transcription process will be long, which is not conducive to the balanced use of computing power. In addition, when the scene is suddenly switched or the volume and tone are suddenly changed, it is easy to be affected by background noise and background music, thus losing information. If the data is too short, the context derivation is easy to lose accuracy. Generally, one file is divided and stored for 30 to 90 seconds. At a normal speaking speed in Mandarin, 90 seconds can contain about 100 to 500 words of text. The text size is moderate and easy to search and compare. The size of a single voice traffic is roughly between 8KB / s and 128KB / s, depending on the audio sampling rate, bit rate, and data accuracy. Assuming that the number of narrowband signals is 32, the upper limit of the size of the 32 files closed in 90 seconds is 32×128K×90=360M, and the upper limit of the size of a single file is 128K×90=11.25M. Under a 100M network speed, it takes about 1 second to complete the transmission of a single file from the device service to the central software. The difference between the first and the last file of the 32 narrowband voices is at least 31 seconds. The transcription process is started during the file queuing and uploading process. The transcription time is roughly in the range of 30 to 50 seconds, that is, in the next 90 seconds of data collection, the transcription process has time margin, and computing resources will not be deeply occupied for a long time. To sum up, after data collection, transmission, text transcription, retrieval and comparison, the entire system delays about 2 minutes to obtain the comparison results within the time period, which balances the network speed and server computing resources and has better efficiency.

[0090] The step (3) specifically comprises the following steps:

[0091] (3.1) Monitor server resources through ssh commands and establish an appropriate number of concurrent threads based on the computing load of the voice transcription process;

[0092] The central software regularly sends vmstat and free commands through the ssh client to monitor the CPU and memory usage of the computing server. According to the test, a Xeon CPU can support the transcription of 5 voice files at the same time, and the memory usage is about 6G.

[0093] (3.2) If the thread is idle, the voice file is retrieved for transcription. Otherwise, wait for the thread to be idle so that it can use computing resources reasonably and avoid server resource overload and downtime.

[0094] Figure 4 The docker container of the server (i.e., the deployment and operation status of the virtual machine) shows the CPU and memory usage of the container virtual machine when two voices are transcribed to text and five voices are transcribed at the same time. The computing resources in this case rely on CPU deployment. A single-core server such as a Xeon 05cpu can deploy 5 voice transcription text containers.

[0095] like Figure 4 As shown in the figure, two files are transcribing text at the same time, and the virtual CPU resource usage of the transcription container is relatively high; the other three containers are idle; when a transcription container is idle, the new transcription process will start to run, so that the server resources always have a certain amount of surplus computing power to avoid downtime.

[0096] Figure 5 This figure shows the actual physical CPU and memory usage of a single-core CPU server when transcribing 5 voice channels simultaneously. Figure 4 and Figure 5 It monitors the computing power of the server. When the container is idle, tasks can be assigned. Otherwise, they will be queued.

[0097] like Figure 5 As shown in the figure, 5-way voice transcription is running simultaneously, and the server physical CPU and memory usage are queried through ssh commands.

[0098] The step (4) specifically comprises the following steps:

[0099] Retrieve the text of voice transcription, bring in semantic feature words for context inference and comparison, collect evidence and alarm on interference frequency, list the frequency and time of interference, and replay voice files retroactively.

[0100] Figure 6 , for the control task data viewing, the upper part of the picture is the broadband spectrum observation (spectrum, signal decision threshold and interference discovery example), where the red part is the semantic interference of the discovery feature (keyword); the lower part of the picture is the parameter list of the interference signal, including frequency, bandwidth, discovery time, number of alarms, and playback and data export of interference voice. This is a functional diagram.

[0101] like Figure 6 As shown in the figure, the two frequencies marked in red show the semantic features of interference alarms by searching and comparing the transcribed texts. The list indicates the occurrence time, frequency, bandwidth and other information. The voice file can be replayed by clicking the play button. Figure 7 The specific implementation scheme of this embodiment can refer to the relevant description in the above embodiment, which will not be repeated here.

[0102] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0103] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0104] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0105] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution device. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0106] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the corresponding program may be stored in a computer-readable storage medium, which, when executed, includes one of the steps of the method embodiment or a combination thereof.

[0107] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0108] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0109] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0110] The method, device, processor and computer-readable storage medium for analyzing and processing aviation communication interference based on semantic recognition of the present invention are adopted to solve the difficulty of manually processing multi-channel narrow-band voice information, and improve the ability to analyze aviation communication interference caused by the FM broadcasting band and the aviation communication band, the adjacent and public use of some frequencies, the aging of high-power equipment in the broadcasting business and illegal installation of stations.

[0111] In this specification, the present invention has been described with reference to specific embodiments thereof. However, it is apparent that various modifications and variations may be made without departing from the spirit and scope of the present invention. Therefore, the specification and drawings should be regarded as illustrative rather than restrictive.

Claims

1. A method for analyzing and processing aviation communication interference based on semantic recognition, characterized in that: The method comprises the following steps: (1) Issue broadcast and aviation communication control tasks, automatically obtain signal parameters, and establish aviation communication voice interference signatures; (2) After the voice data is filtered, the stream data is cut and stored into several files, which serve as data buffers for the transcription process; (3) Adjust the concurrency of file transcription based on the computing load of the voice transcription process; (4) Retrieve the text of the voice transcription, bring in semantic feature words for contextual inference and comparison, and obtain evidence and issue an alarm for the interference frequency.

2. The method for analyzing and processing aviation communication interference based on semantic recognition according to claim 1 is characterized in that: The step (1) specifically comprises the following steps: (1.1) When the voice on the aviation communication frequency is interfered by broadcasting, the broadcasting interference voice feature words are entered into the text retrieval database; a 24-hour continuous monitoring task of the broadcasting and aviation communication frequency band is issued, and the signal parameters exceeding the adaptive threshold are given; (1.2) Send the frequency, bandwidth and signal modulation mode of the narrowband signal parameters to the monitoring receiver; (1.3) For signal parameter changes caused by abnormal signals, automatically modify the multi-channel narrowband monitoring parameters and continue with step (1.2).

3. The method for analyzing and processing aviation communication interference based on semantic recognition according to claim 1, characterized in that: The step (2) specifically comprises the following steps: After the voice data is filtered, the PCM stream data is divided by time length and stored as WAV voice files according to the efficiency of the voice transcription process and the text size; the closed voice files are asynchronously uploaded through the URL address.

4. The method for analyzing and processing aviation communication interference based on semantic recognition according to claim 1, characterized in that: The step (3) specifically comprises the following steps: (3.1) Monitor server resources through ssh commands and establish an appropriate number of concurrent threads based on the computing load of the voice transcription process; (3.2) If the thread is idle, retrieve the voice file for transcription; otherwise, wait for the thread to be idle.

5. The method for analyzing and processing aviation communication interference based on semantic recognition according to claim 1, characterized in that: The step (4) specifically comprises the following steps: Retrieve the text of voice transcription, bring in semantic feature words for context inference and comparison, collect evidence and alarm on interference frequency, list the frequency and time of interference, and replay voice files retroactively.

6. A device for realizing aviation communication interference analysis and processing based on semantic recognition, characterized in that: The device comprises: a processor configured to execute computer-executable instructions; A memory storing one or more computer executable instructions, wherein when the computer executable instructions are executed by the processor, each step of the method for analyzing and processing aviation communication interference based on semantic recognition as described in any one of claims 1 to 5 is implemented.

7. A processor for implementing aviation communication interference analysis and processing based on semantic recognition, characterized in that: The processor is configured to execute computer executable instructions. When the computer executable instructions are executed by the processor, the various steps of the method for realizing aviation communication interference analysis and processing based on semantic recognition as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program can be executed by a processor to implement the various steps of the method for realizing aviation communication interference analysis and processing based on semantic recognition as described in any one of claims 1 to 5.

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